Learn how semantic publishing can personalize user experience by delivering contextual content based on NLP, search history, user profiles and semantically enriched data.
Over the centuries, globalization and various technologies have profoundly changed the way we consume news.
Just as a brief comparison, in Medieval times messengers rode far and wide to deliver news and rulers used town criers to inform the (predominantly illiterate) population about the latest laws and local taxation bills. Today, most people around the world have direct access to vast amounts of information and political institutions use social media to engage voters.
Technology is steadily transforming the way we experience news. It seems only yesterday when we relied on reading the newspaper in the morning and watching TV news in the evening to catch up with local and world events. Nowadays, consumers are constantly exposed to news and news outlets are reaching their audiences through media platforms, mobile apps, email newsletters, social media, podcasts, etc.
In this overflow of news and information, media publishers have to go the extra mile to keep users engaged and willing to come back to their online platforms. Just as in Medieval times the town criers dressed in bright colors to catch the eye, media publishers today are applying various strategies to attract readers’ attention. They are also relying on different technologies to be able to accommodate their readers’ interests by recommending relevant content while also looking to maximize ad revenues by serving relevant ads.
A recent report from The Reuters Institute for the Study of Journalism – What do News Readers Really Want to Read about – shows that, in our high-choice media culture, people rely most of all on a notion of personal relevance to choose the news they consume.
Thanks to solutions based on semantic technology, media publishers are able to better engage their readers with the help of sophisticated tools like user-focused recommendations, sentiment analysis and more. These are also the major components of the multi-faceted solution developed by semantic technology expert Ontotext to meet media publishers’ needs.
How does it work? A semantic annotation service, with the help of a knowledge base, automatically tags content and extracts specific information from the text, which is later used by the other services in the stack. In the meantime, a sentiment analysis service evaluates how users feel about and react to certain concepts, people, products or topics, based on the comments they post.
Another major component of Ontotext’s solution is the recommendation services based on the user profiles. They take into consideration various factors such as the semantic fingerprints of the content a user has read and actively engaged with, their liking and disliking of content provided by other users and any other sentiments expressed.
Finally, to help media publishers improve their control of the serving of ads and their relevance to the users, Ontotext has built a custom ad serving platform. With the help of semantic analysis, the platform selects out of several candidates the ad that matches best the user’s activity and preferences.Simply put, the more media publishers know about how users consume their content, the more relevant their content and ad recommendations will become. Which is the shortest path to higher user engagement and boosted ad revenues. Click To Tweet
Of course, as technology continues to get integrated more and more into our lives, the way we navigate the news environment and what drives our interests will continue to evolve.
Read our case study to see how semantic publishing helps media publishers keep users happy or discuss your particular use case with us.